We consider concurrent games played on graphs. At every round of a game, each
player simultaneously and independently selects a move; the moves jointly
determine the transition to a successor state. Two basic objectives are the
safety objective to stay forever in a given set of states, and its dual, the
reachability objective to reach a given set of states. We present in this paper
a strategy improvement algorithm for computing the value of a concurrent safety
game, that is, the maximal probability with which player~1 can enforce the
safety objective. The algorithm yields a sequence of player-1 strategies which
ensure probabilities of winning that converge monotonically to the value of the
safety game.
Our result is significant because the strategy improvement algorithm
provides, for the first time, a way to approximate the value of a concurrent
safety game from below. Since a value iteration algorithm, or a strategy
improvement algorithm for reachability games, can be used to approximate the
same value from above, the combination of both algorithms yields a method for
computing a converging sequence of upper and lower bounds for the values of
concurrent reachability and safety games. Previous methods could approximate
the values of these games only from one direction, and as no rates of
convergence are known, they did not provide a practical way to solve these
games